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[GH-ISSUE #2838] [langgraph]: Help in deciding What to use for a workflow #2686

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opened 2026-06-05 17:26:17 -04:00 by yindo · 1 comment
yindo commented 2026-06-05 17:26:17 -04:00
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Originally created by @MINEGHOST007 on GitHub (Feb 27, 2026).
Original GitHub issue: https://github.com/langchain-ai/docs/issues/2838

Type of issue

request for content

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Python

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Image

any examples for this

Originally created by @MINEGHOST007 on GitHub (Feb 27, 2026). Original GitHub issue: https://github.com/langchain-ai/docs/issues/2838 ### Type of issue request for content ### Language Python ### Description <img width="1600" height="768" alt="Image" src="https://github.com/user-attachments/assets/53f47369-1d30-430c-8a29-c68de87b787c" /> any examples for this
yindo added the langgraphexternal labels 2026-06-05 17:26:17 -04:00
yindo commented 2026-06-05 17:26:18 -04:00
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@Rajathbharadwaj commented on GitHub (Mar 14, 2026):

Here's a quick guide for choosing between these patterns:

LangGraph (Recommended for most cases)

  • Use when you need explicit control over agent flow
  • Best for: Multi-step agents, human-in-the-loop, complex branching
  • Example: Customer support bot that routes to specialists

LCEL (LangChain Expression Language)

  • Use for simple, linear chains
  • Best for: Straightforward prompt → LLM → output flows
  • Not ideal for agents that need loops or branching

create_react_agent

  • Quick way to spin up a ReAct agent
  • Good for prototypes
  • For production, often better to use LangGraph directly for more control

Decision tree:

  1. Do you need loops or branching? → LangGraph
  2. Is it a simple chain? → LCEL
  3. Quick prototype with tools? → create_react_agent
  4. Need human approval checkpoints? → LangGraph with interrupt_before
  5. Multi-agent collaboration? → LangGraph with separate nodes per agent

For ready-to-use patterns, I put together an MCP server that provides these templates directly to Claude/Cursor: https://github.com/Rajathbharadwaj/langgraph-patterns-mcp

Hope this helps!

<!-- gh-comment-id:4059581227 --> @Rajathbharadwaj commented on GitHub (Mar 14, 2026): Here's a quick guide for choosing between these patterns: **LangGraph (Recommended for most cases)** - Use when you need explicit control over agent flow - Best for: Multi-step agents, human-in-the-loop, complex branching - Example: Customer support bot that routes to specialists **LCEL (LangChain Expression Language)** - Use for simple, linear chains - Best for: Straightforward prompt → LLM → output flows - Not ideal for agents that need loops or branching **create_react_agent** - Quick way to spin up a ReAct agent - Good for prototypes - For production, often better to use LangGraph directly for more control **Decision tree:** 1. Do you need loops or branching? → LangGraph 2. Is it a simple chain? → LCEL 3. Quick prototype with tools? → create_react_agent 4. Need human approval checkpoints? → LangGraph with interrupt_before 5. Multi-agent collaboration? → LangGraph with separate nodes per agent For ready-to-use patterns, I put together an MCP server that provides these templates directly to Claude/Cursor: https://github.com/Rajathbharadwaj/langgraph-patterns-mcp Hope this helps!
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Reference: langchain-ai/docs#2686
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